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Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China

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Journal of Integrative Agriculture 2024年第1期23卷 283-297页

作者： Jie Xue Xianglin Zhang songchao chen Bifeng Hu Nan Wang Zhou Shi Department of Land Management Zhejiang UniversityHangzhou 310058China Institute of Applied Remote Sensing and Information Technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang UniversityHangzhou 311215China Department of Land Resource Management School of Public Finance and Public AdministrationJiangxi University of Finance and EconomicsNanchang 330013China Key Laboratory of Data Science in Finance and Economics Jiangxi University of Finance and EconomicsNanchang 330013China Key Laboratory of Spectroscopy Sensing Ministry of Agriculture and Rural AffairsHangzhou 310058China

Various land use and land cover(LULC)products have been produced over the past decade with the development of remote sensing *** the differences in LULC classification schemes,there is a lack of research on assessing the accuracy of their application to croplands in a unified ***,this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products(i.e.,MCD12Q1V6,GlobCover2009,FROM-GLC and GlobeLand30)based on the harmonised FAO criterion,and quantified the relationships between four factors(i.e.,slope,elevation,field size and crop system)and cropland classification *** validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency,with overall accuracies of 94.90 and 93.52%,*** FROMGLC showed the worst performance,with an overall accuracy of 83.17%.Overlaying the cropland generated by the four global LULC products,we found the proportions of complete agreement and disagreement were 15.51 and 44.72% for the cropland classification,*** consistency was mainly observed in the Northeast China Plain,the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain,*** contrast,low consistency was detected primarily on the eastern edge of the northern and semiarid region,the Yunnan-Guizhou Plateau and southern *** size was the most important factor for mapping *** area accuracy,compared with China Statistical Yearbook data at the provincial scale,the accuracies of different products in descending order were:GlobeLand30,FROM-GLC,MCD12Q1,and *** cropland classification schemes mainly caused large area deviations among the four products,and they also resulted in the different ranks of spatial accuracy and area accuracy among the four *** results can provide valuable suggestions for selecting cropland products at the national or provinc

关键词： global LULC products cropland mapping accuracy evaluation food security China

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Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

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Journal of Integrative Agriculture 2024年第8期23卷 2820-2841页

作者： Xianglin Zhang Jie Xue songchao chen Zhiqing Zhuo Zheng Wang Xueyao chen Yi Xiao Zhou Shi Institute of Applied Remote Sensing and Information Technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Department of Land Management Zhejiang UniversityHangzhou 310058China ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang UniversityHangzhou 311215China Institute of Digital Agriculture Zhejiang Academy of Agricultural SciencesHangzhou 310021China Key Laboratory of Spectroscopy Sensing Ministry of Agriculture and Rural AffairsHangzhou 310058China

Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management *** a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different ***,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human *** overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in *** results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on *** the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to *** recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average *** the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final *** the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping

关键词： cropland soil organic matter digital soil mapping machine learning feature selection model averaging

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Remote sensing of soil degradation:Pro gress andperspective

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International Soil and Water Conservation Research 2023年第3期11卷 429-454页

作者： Jingzhe Wang Jianing Zhen Weifang Hu songchao chen Ivan Lizaga Mojtaba Zeraatpisheh Xiaodong Yang School of Artificial Intelligence Shenzhen PolytechnicShenzhen518055China State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing100101China Key Laboratory of Wetland Ecology and Environment Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun130102China Institute of Agricultural Resources and Environment Guangdong Academy of Agricultural SciencesGuangzhou510640China ZJU-Hangzhou Global Scientific and Technological Innovation Center Hangzhou311200China Isotope Bioscience Laboratory-ISOFYS Department of Green Chemistry and TechnologyGhent UniversityCoupure Links 6539000GhentBelgium Rubenstein School of Environment and Natural Resources University of Vermont81 Carrigan DriveBurlingtonVT05405USA Gund Institute for Environment University of Vermont210 Colchester AveBurlingtonVT05401USA Department of Geography and Spatial Information Technology Ningbo UniversityNingbo315211China

Soils constitute one of the most critical natural resources and maintaining their health is vital for agricultural development and ecological sustainability,providing many essential ecosystem *** by climatic variations and anthropogenic activities,soil degradation has become a global issue that seriously threatens the ecological environment and food *** sensing(RS)technologies have been widely used to investigate soil degradation as it is highly efficient,time-saving,and *** review encompasses recent advances and the state-of-the-art of ground,proximal,and novel Rs techniques in soil degradation-related *** reviewed the RS-related indicators that could be used for monitoring soil degradation-related *** direct indicators(mineral composition,organic matter,surface roughness,and moisture content of soil)and indirect proxies(vegetation condition and land use/land cover change)for evaluating soil degradation were comprehensively *** results suggest that these above indicators are effective for monitoring soil degradation,however,no indicators system has been established for soil degradation monitoring to *** also discussed the RS's mechanisms,data,and methods for identifying specific soil degradation-related phenomena(e.g.,soil erosion,salinization,desertification,and contamination).We investigated the potential relations between soil degradation and Sustainable Development Goals(SDGs)and also discussed the challenges and prospective use of RS for assessing soil *** further advance and optimize technology,analysis and retrieval methods,we identify critical future research needs and directions:(1)multi-scale analysis of soil degradation;(2)availability of RS data;(3)soil degradation process modelling and prediction;(4)shared soil degradation dataset;(5)decision support systems;and(6)rehabilitation of degraded soil resource and the contribution of RS *** it is difficult to moni

关键词： Soil degradation Remote sensing Soil properties Earth observation Sustainable development goals

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Most root-derived carbon inputs do not contribute to long-term global soil carbon storage

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Science China Earth Sciences 2023年第5期66卷 1072-1086页

作者： Guocheng WANG Liujun XIAO Ziqi LIN Qing ZHANG Xiaowei GUO Annette COWIE Shuai ZHANG Mingming WANG songchao chen Ganlin ZHANG Zhou SHI Wenjuan SUN Zhongkui LUO Institute of Agriculture Remote Sensing and Information Technology College of Environmental and Resource SciencesZhejiang UniversityHangzhou310058China LAPC Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing100029China School of Atmospheric Sciences Guangdong Province Key Laboratory for Climate Change and Natural Disaster StudiesSun Yat-sen UniversityZhuhai519082China New South Wales Department of Primary Industries University of New EnglandArmidaleNSW2351Australia State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing210008China Academy of Ecological Civilization Zhejiang UniversityHangzhou310058China Key Laboratory of Environment Remediation and Ecological Health Ministry of EducationZhejiang UniversityHangzhou310058China State Key Laboratory of Vegetation and Environmental Change Institute of BotanyChinese Academy of SciencesBeijing100093China Key Laboratory of Agricultural Remote Sensing and Information System Zhejiang ProvinceHangzhou310058China

Plant root-derived carbon(C)inputs(I_(root))are the primary source of C in mineral bulk ***,a fraction of I_(root)may lose quickly(I_(loss),e.g.,via rhizosphere microbial respiration,leaching and fauna feeding)without contributing to long-term bulk soil C storage,yet this loss has never been quantified,particularly on a global *** this study we integrated three observational global data sets including soil radiocarbon content,allocation of photo synthetically assimilated C,and root biomass distribution in 2,034 soil profiles to quantify I_(root)and its contribution to the bulk soil C *** show that global average I_(root)in the 0-200 cm soil profile is 3.5 Mg ha^(-1)yr^(-1),~80%of which(i.e.,I_(loss))is lost rather than co ntributing to long-term bulk soil C storage.I_(root)decreases exponentially with soil depth,and the top 20 cm soil contains>60%of total I_(root).Actual C input contributing to long-term bulk soil storage(i.e.,I_(root)-I_(loss))shows a similar depth distribution to I_(root).We also map I_(loss)and its depth distribution across the *** results demonstrate the global significance of direct C losses which limit the contribution of I_(root)to bulk soil C storage;and provide spatially explicit data to facilitate reliable soil C predictions via separating direct C losses from total root-derived C inputs.

关键词： Carbon inputs Root biomass Soil organic carbon Depth distribution Bulk soil carbon Radiocarbon

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Hand-feel soil texture observations to evaluate the accuracy of digital soil maps for local prediction of soil particle size distribution:A case study in Central France

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Pedosphere 2023年第5期33卷 731-743页

作者： Anne C.RICHER-de-FORGES Dominique ARROUAYS Laura POGGIO songchao chen Marine LACOSTE Budiman MINASNY Zamir LIBOHOVA Pierre ROUDIER Vera LMULDER HervéNÉDÉLEC Guillaume MARTELET Blandine LEMERCIER Philippe LAGACHERIE Hocine BOURENNANE INRAE(Institut national de recherche pour l'agriculture l'alimentation et l'environnement)Info&Sols UnitOrléans 45075France ISRIC(International Soil Reference and Information Centre)Wageningen P.O.Box 353Wageningen 6700The Netherlands Zhejiang University-Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311200China The University of Sydney Sydney Institute of Agriculture.Eveleigh NSW 2015Australia The University of Sydney School of Life and Environmental SciencesEveleigh NSW 2015Australia USDA-ARS(United States Department of Agriculture-Agricultural Research Service) Dale Bumpers Small Farms Research Center6883 S.State Hwy.23Booneville AR 72927USA Landcare Research-Manaaki Whenua Palmerston North 4442New Zealand Soil Geography and Landscape Group Wageningen UniversityP.O.Box 47Wageningen 6700The Netherlands Chambre d'Agriculture du Loiret Orléans F-45000France Bureau de Recherches Géologiques et Minières BP 36009Orléans cedex 2Orléans 45060France UMR SAS(UnitéMixte de Recherche"Sol Agro et hydrosystème Spatialisation")Institut Agro INRAERennes F-35000France UMR LISAH(UnitéMixte de Recherche"Laboratoire d'Etude des Interactions entre Sol-Agrosystème-Hydrosystème") INRAEInstitut AgroIRD(Institut de Recherche pour le Développement)Montpellier F-34000France

Digital maps of soil properties are now widely ***-users now can access several digital soil mapping(DSM)products of soil properties,produced using different models,calibration/training data,and covariates at various spatial scales from global to ***,there is an urgent need to provide easy-to-understand tools to communicate map uncertainty and help end-users assess the reliability of DSM products for use at local *** this study,we used a large amount of hand-feel soil texture(HFST)data to assess the performance of various published DSM products on the prediction of soil particle size distribution in Central *** tested four DSM products for soil texture prediction developed at various scales(global,continental,national,and regional)by comparing their predictions with approximately 3200 HFST observations realized on a 1:50000 soil survey conducted after release of these DSM *** used both visual comparisons and quantitative indicators to match the DSM predictions and HFST *** comparison between the low-cost HFST observations and DSM predictions clearly showed the applicability of various DSM products,with the prediction accuracy increasing from global to regional *** simple evaluation can determine which products can be used at the local scale and if more accurate DSM products are required.

关键词： digital soil mapping products easy-to-understand tool hand-feel observation local use map uncertainty prediction performance spatial extent visual assessment

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基于机器学习的江汉平原土壤有机碳预测及制图

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农业资源与环境学报 2023年第3期40卷 644-650页

作者：沈佳丽陈颂超胡碧峰李硕华中师范大学地理过程分析与模拟湖北省重点实验室武汉430079 浙江大学杭州国际科创中心杭州311200 江西财经大学旅游与城市管理学院南昌330013

土壤有机碳(SOC)不仅显著响应于表层,而且随深度的变化呈现不同的响应。江汉平原作为长江经济带农田生态系统的重要组成部分,其SOC垂向分布状况仍有待考察。本研究收集了2009-2012年湖北省土系调查的66个剖面数据,基于9个环境因子为协... 详细信息

土壤有机碳(SOC)不仅显著响应于表层,而且随深度的变化呈现不同的响应。江汉平原作为长江经济带农田生态系统的重要组成部分,其SOC垂向分布状况仍有待考察。本研究收集了2009-2012年湖北省土系调查的66个剖面数据,基于9个环境因子为协变量使用随机森林法构建0~30、>30~60、>60~100 cm土层深度的SOC含量预测模型,绘制了30 m空间分辨率的SOC含量分布图,并估算了SOC储量。结果表明,SOC含量随土层深度的增加而减少,总体呈中东部高、西部低的特征。模型对表层(0~30 cm)SOC的预测精度最高(R^(2)=0.45,RMSE=3.28 g·kg^(-1)),温度、黏粒含量和降水对模型重要性居前三。江汉平原1 m深SOC储量为183.75 Tg,>30~100 cm土层SOC储量约占1 m深度总储量的59%。因此,土壤碳库估算及固碳潜力评估时需着重考虑深层土壤。本研究可为掌握SOC空间分布及垂直分异的响应规律提供参考。

关键词：碳库土壤-景观模型机器学习环境因子深层土壤

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Meridional deflection of global eddy propagation derived from tandem altimetry: Mechanism and implication

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Science China Earth Sciences 2024年第3期67卷 811-825页

作者： Ge chen Xiaoyan chen Frontiers Science Center for Deep Ocean Multispheres and Earth System School of Marine TechnologyOcean University of ChinaQindao 266100China Laboratory for Regional Oceanography and Numerical Modeling Laoshan LaboratoryQindao 266237China

A common view on meridional deflection of eddy propagation is poleward for cyclones and equatorward for anticyclones. This widely accepted polarity-sensitive pattern has been increasingly undermined given that it is systematically violated on both zonal and regional scales as recently reported. Here, we approach the problem by exploring these violations in terms of eddy effects of spatiotemporal geostrophy, thermal fading, and flow dragging, yielding the following main conclusions.(1) The polarity-dependent deflection discrepancy is a pseudo feature resulting from a biased fit to the normalized eddy tracks which are spatially asymmetric(though azimuthally symmetric) between the two signs;Instead, the primary pattern of eddy deflection appears to be geographically correlated and polarity independent.(2) Geostrophic adjustment plays a critical role in defining the meridional movement of an eddy. Specifically, a consistent poleward(equatorward) trajectory bending of spatially(temporally) ageostrophic eddies is observed irrespective of their polarity.(3) The mechanism of eddy deflection is also determined by its zonal propagation direction. Westward propagating eddies are substantially affected by thermal fading, while opposite ones by flow dragging. A realistic and comprehensive understanding of eddy deflection mechanisms serves as a significant contribution to the prediction of eddy trajectory, and the protection of ocean environment.

关键词： Mesoscale eddies Eddy propagation Eddy meridional deflection Satellite observation Geostrophic adjustment

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A refined representation method of the particle size distribution curve based on grading entropy

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Particuology 2024年第5期88卷 302-311页

作者： Xing Li Qun chen Zhaozhao Liu cheng Zhou chen Wang chen chen State Key Laboratory of Hydraulics and Mountain River Engineering College of Water Resource and HydropowerSichuan UniversityChengdu610065China

The particle size distribution(PSD)curve is an important expression of the basic properties of the *** characteristic parameters such as median particle size D_(50),effective particle size D_(10),and some combinations of characteristic parameters can only represent some points of the PSD curve,failing to represent all information of the PSD *** this paper,a fraction characteristic parameter F that could reflect the fraction size variation of the PSD curve was introduced based on grading *** a new presentation method of the A-B-F three parameters was proposed for a refined representation of the PSD *** was found that the newly constructed model not only better represents the differences in the width of PSD curves but also has a higher sensitivity than the A-B two-parameter model proposed by Lő*** PSD curves with similar distributions,the new presentation method has a higher degree of discrimination than that of the D_(50)-C_(u)-C_(c) three-parameter or the four-parameter combination G_(c) proposed by ***,the application of this new method in describing the spatial nonuniformity distribution of depositions and predicting the soil hydraulic conductivity was *** research results can provide a reference for the refined representation of PSD curves.

关键词： Grading entropy Particle size distribution curve Refined representation

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Track correlation algorithm based on CNN-LSTM for swarm targets

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Journal of Systems Engineering and Electronics 2024年第2期35卷 417-429页

作者： chen Jinyang WANG Xuhua chen Xian Research Institute for National Defense Engineering Academy of Military SciencesLuoyang 471023China Information Engineering University Zhengzhou 450001China School of Computer Science and Technology Xidian UniversityXi’an 710071China

The rapid development of unmanned aerial vehicle(UAV) swarm, a new type of aerial threat target, has brought great pressure to the air defense early warning system. At present, most of the track correlation algorithms only use part of the target location, speed, and other information for *** this paper, the artificial neural network method is used to establish the corresponding intelligent track correlation model and method according to the characteristics of swarm ***, a route correlation method based on convolutional neural networks (CNN) and long short-term memory (LSTM)Neural network is designed. In this model, the CNN is used to extract the formation characteristics of UAV swarm and the spatial position characteristics of single UAV track in the formation,while the LSTM is used to extract the time characteristics of UAV swarm. Experimental results show that compared with the traditional algorithms, the algorithm based on CNN-LSTM neural network can make full use of multiple feature information of the target, and has better robustness and accuracy for swarm targets.

关键词： track correlation correlation accuracy rate swarm target convolutional neural network(CNN) long short-term memory(LSTM)neural network

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Two-stage Planning Method for Energy Router Considering Its Optimal Operation in Distribution Networks

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 605-616页

作者： Meifu chen Mingchao Xia Qifang chen School of Electrical Engineering Beijing Jiaotong UniversityBeijing 100044China

An energy router can effectively optimize the network loss and power quality of distribution networks. The optimal configuration of the energy router is relatively complex because issues dynamically influence each other, such as the location of the energy router, optimal number and capacity of its ports, and building new distribution lines for the ports. Presently, there has been very few research studies on the practical problems for the energy router. In this paper, a planning model of an energy router combined with the distribution network is established, which fully exploits the active and reactive power control abilities of the energy router to optimize the operation of the grid. The configuration problem is decoupled into two stages. The upper layer determines the location of the energy router and the parameters of the candidate new distribution lines for the ports. The lower layer calculates the optimal configuration of the energy router by minimizing the total annual cost. Because of the same rated bus voltage in the distribution network, the existing structure of the energy router is changed to be more applicable for the distribution network, and then the power flow model of the energy router is also modified. Due to the nonlinearity of the model, the planning model is converted into a mixed-integer second-order cone model to solve efficiently. In addition, some core factors influencing the optimal scheme of the energy router are also analyzed in this paper. Simulation results show that the optimal scheme of the energy router can significantly improve the economic deployment of the energy router, and optimize the network loss and power quality of the distribution network.

关键词： Capacity allocation distribution network energy router optimal operation

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